Hepatocellular carcinoma (HCC) is the most common type of liver cancer, and is responsible for an estimated 660,000 deaths worldwide. It is believed that HCC develops upon significant damage to the cellular machinery in the liver after sustained viral infections or cirrhosis. Hepatitis C virus (HCV) infection is of particular interest since an estimated 130-170 million people are infected with the virus. It is believed that HCV infection causes 25% of all reported cases of HCC. HCV viral infections can be currently diagnosed with an HCV antibody enzyme immunoassays but such testing cannot distinguish between acute and chronic infections. If a set of reliable biomarkers were available that can effectively identify HCV infected individuals who are in the early stages of HCC and potentially more receptive to treatments.
Metabolomics, in which a large number of small molecule metabolites are detected quantitatively, often in easily accessible biofluids such as blood and urine, can provide useful information regarding early biomarkers and altered metabolic pathways. As metabolites are the downstream products of genes and gene expression, they integrate many of the alterations caused by disease or other biological stresses. Metabolites are exquisitely sensitive to different biological states and therefore represent a promising approach to identify potential biomarkers. Several analytical techniques such as nuclear magnetic resonance (NMR), liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) have been used to detect metabolic changes in a number of cancers including liver cancer. Several studies using a variety of analytical techniques have reported discovery of potential biomarkers in biological samples such as serum, plasma and urine of subjects with HCC relative to healthy controls. However, none of the studies have focused exclusively on altered metabolic pathways between HCV patients, who have high risk of developing HCC, and those who have developed HCC.
Metabolomics thus provides a powerful approach to identify small molecule biomarkers associated with cancer and other diseases. By focusing on the concentrations and fluxes of low molecular weight metabolites (<˜1000 m/z) in biofluids, detailed information on biological systems and their concordant correlations across related disease states can be obtained.
The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education. The database is designed to contain or link three kinds of data: 1) chemical data, 2) clinical data, and 3) molecular biology/biochemistry data. The database (version 3.5) contains 40,446 metabolite entries including both water-soluble and lipid soluble metabolites as well as metabolites that would be regarded as either abundant (>1 μM) or relatively rare (<1 nM). Additionally, 5,235 protein (and DNA) sequences are linked to these metabolite entries. See Wishart, D. S., Tzur, D., Knox, C., et al., HMDB: the Human Metabolome Database, Nucleic Acids Res. 2007 January; 35(Database issue):D521-6; Wishart, D. S., Knox, C., Guo, A. C., et al., HMDB: a knowledgebase for the human metabolome, Nucleic Acids Res. 2009 37(Database issue):D603-610; Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., et al., HMDB 3.0—The Human Metabolome Database in 2013, Nucleic Acids Res. 2013. January 1; 41(D1):D801-7.